0% Complete
صفحه اصلی
/
4th international edition and 13th Iranian Conference on Bioinformatics
A computational approach to identify the biomarker based on the RNA sequencing data analysis for Alzheimer’s disease
نویسندگان :
Atena Vaghf
1
Shahram Tahmasebian
2
Nayereh Abdali
3
1- Student Research Committee, Shahrekord University of Medical Sciences, Shahrekord, Iran
2- Department of Medical Biotechnology, School of Advanced Technologies, Shahrekord University of Medical Sciences, Shahrekord, Iran
3- Student Research Committee, Shahrekord University of Medical Sciences, Shahrekord, Iran
کلمات کلیدی :
Alzheimer’s disease،RNA sequencing،miR-9-5p،GABRB2
چکیده :
Introduction: Alzheimer’s disease (AD) is a progressive neurodegenerative disease. AD affects at least 27 million people and is associated with a high impact on the life of the patient’s family and a huge financial cost to society. RNA sequencing (RNA-seq) is one effective approach to finding the heterogeneous gene expressions of diseases that helps discover new functional genes as prognostic biomarkers. Besides, It is well-known that microRNA (miRNAs) biomarkers have emerged as a powerful screening tool, as they are highly expressed in CRC patients and easily detectable in several biological samples. The bioinformatics method is cost-effective and time-saving when studying the role of miRNAs-mRNA. Therefore, in this study computational models were used to identify AD-related biomarker by RNA-seq analysis. Methods: The RNA sequencing of 40 AD samples with 8 healthy control tissue from the occipital lobe under the accession code GSE203206 were obtained from the GEO database (https://www.ncbi.nlm.nih.gov/geo/). The differentially expressed genes (DEGs) between AD and normal tissues were obtained by using GEO2R. The 1000 top up regulated genes were imported into the STRING (version 12.0, http://string-db.org) database to identify the interactive association between the proteins. Then, the all interactions with a significant combined score >0.4 were selected for further analysis. The appropriate gene with the highest degrees of connectivity were selected as hub genes. The targetSacn database is a specialized collection of microRNA-mRNA targeting relationships. These databases were used to obtain hub gene-associated miRNA. Results: This study identified 4150 genes with |log2FC|>0.5 and P-value <0.01 as DEGs: 1279 upregulated and 2871 downregulated genes. γ-aminobutyric acid receptors β2 subunit gene (GABRB2) was identified as one of the best hub gene in STRING which hsa-miR-9-5p can suppressed the GABRB2 expression in AD. GABRB2 has a pivotal role in the central nervous system. Several studies also reported alterations in GABA levels, typically a reduction in total neurotransmitter concentration in several regions of the post-mortem AD brain. As recorded, miR-9-5p is found to be downregulated in the brain of the AD patients. Overexpression of miR-9-5p modulates neuroinflammation in the central nervous system. Of note, this bioinformatic results confirmed that targeting GABRB2 is an important mechanism of AD function improving by miR-9-5p in AD. Moreover, TargetScan indicating that the seed region of miR-9-5p contains 2 complementary sites within position 4645-4652 and 4726-4732 of GABRB2 3' UTR. Conclusion: Taken together, our findings from RNA sequencing analysis provide the first clues regarding the role of miR-9-5p as a modulator the progression of AD by inhibiting GABRB2 translation. The results also provide valuable insights into the regulation of miR-9-5p and GABRB2 for future research and therapeutic development. These can be used as a specific diagnostic index and therapeutic target for patients with AD.
لیست مقالات
لیست مقالات بایگانی شده
Analysis of enrichment pathways and ontology of genes related to Feed efficiency in sheep
Mehre Mohammadnezhad - Mohsen Gholizadeh
Solving Diffusion Equations Using Physics-Informed Neural Networks: A Biological Application
Yasaman Razzaghi - Ali Shokri - Ahmad Aliyari Boroujeni
Comprehensive Multi-Omics Analysis Reveals NPC2 and ITGAV Genes as Potential Prognostic Biomarkers in Gastrointestinal Cancers
Mohammad Reza Zabihi - Moein Piroozkhah - Pooya Jalali - Zahra Salehi
In silico analysis of Maize WRKY transcription factors in response to drought and salt stress
Majid NorouzI - Sahar Shahgoli - Bahram Baghban Kohnehrouz
Dissecting the impact of smoking on epigenetic mechanisms that influencing Lung cancer susceptibility
Mahboobeh Golchinpour - Alireza Fotuhi Siahpirani
Exploring Vaginal Microbiome Diversity in Early Pregnancy: Implications for Healthy Pregnancy and Miscarriage
Nasrin Vatankhah Hagigi - Mohammad Hossein Norouzi-Beirami
Molecular Docking Analysis of Eugenol and Paclitaxel Targeting MRAS in Breast Cancer Therapy
Yaas Rowhani - Somayeh Reiisi
Minimum Error Entropy: A Superior Alternative to Mean Square Error for Heavy-Tailed EEG Signal Classification
Shermin Shahbazi - Hossein Mohammadi
New inhibitors of the Toxoplasmosis by in-silico drug repurposing
Milad Jaberi - Masoud Aliyar - Mosleh Kadkhodamohammadi - Parva Karimimousivandi
Identification of circRNA-miRNA-mRNA Interaction in Myocardial Infarction
Amir Hesam Pahlevani - Ashkan Nazari - Kiarash Zare - Mohammad Ghorbani - Abdolhakim Aalkamel - Mohammad Mehdi Naghizadeh
بیشتر
ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 42.7.0